Deep learning-based joint detection in Rheumatoid arthritis hand radiographs.

Autor:	Fung DL; Department of Computer Science., Liu Q; Department of Computer Science.; Department of Statistics.; Department of Biochemistry and Medical Genetics., Islam S; Department of Computer Science., Lac L; Department of Computer Science.; Department of Statistics., O'Neil L; Department of Internal Medicine, University of Manitoba, Winnipeg, MB, Canada., Hitchon CA; Department of Internal Medicine, University of Manitoba, Winnipeg, MB, Canada., Hu P; Department of Computer Science.; Department of Biochemistry and Medical Genetics.; Department of Biochemistry, Western University, London, ON, Canada.
Jazyk:	angličtina
Zdroj:	AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science [AMIA Jt Summits Transl Sci Proc] 2023 Jun 16; Vol. 2023, pp. 206-215. Date of Electronic Publication: 2023 Jun 16 (Print Publication: 2023).
Abstrakt:	Advancements in technology have enabled diverse tools and medical devices that are able to improve the efficiency of diagnosis and detection of various health diseases. Rheumatoid arthritis is an autoimmune disease that affects multiple joints including the wrist, hands and feet. We used YOLOv5l6 to detect these joints in radiograph images. In this paper, we show that training YOLOv5l6 on joint images of healthy patients is able to achieve a high performance when used to evaluate joint images of patients with rheumatoid arthritis, even when there is a limited number of training samples. In addition to training joint images from healthy individuals with YOLOv5l6, we added several data augmentation steps to further improve the generalization of the deep learning model. (©2023 AMIA - All rights reserved.)
Databáze:	MEDLINE
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